Computer vision Books

Book SynopsisTable of ContentsI IMAGE FORMATION 1 1 Geometric Camera Models 3 1.1 Image Formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.1.1 Pinhole Perspective . . . . . . . . . . . . . . . . . . . . . . . 4 1.1.2 Weak Perspective . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.1.3 Cameras with Lenses . . . . . . . . . . . . . . . . . . . . . . . 8 1.1.4 The Human Eye . . . . . . . . . . . . . . . . . . . . . . . . . 12 1.2 Intrinsic and Extrinsic Parameters . . . . . . . . . . . . . . . . . . . 14 1.2.1 Rigid Transformations and Homogeneous Coordinates . . . . 14 1.2.2 Intrinsic Parameters . . . . . . . . . . . . . . . . . . . . . . . 16 1.2.3 Extrinsic Parameters . . . . . . . . . . . . . . . . . . . . . . . 18 1.2.4 Perspective Projection Matrices . . . . . . . . . . . . . . . . . 19 1.2.5 Weak-Perspective Projection Matrices . . . . . . . . . . . . . 20 1.3 Geometric Camera Calibration . . . . . . . . . . . . . . . . . . . . . 22 1.3.1 ALinear Approach to Camera Calibration . . . . . . . . . . . 23 1.3.2 ANonlinear Approach to Camera Calibration . . . . . . . . . 27 1.4 Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2 Light and Shading 32 2.1 Modelling Pixel Brightness . . . . . . . . . . . . . . . . . . . . . . . 32 2.1.1 Reflection at Surfaces . . . . . . . . . . . . . . . . . . . . . . 33 2.1.2 Sources and Their Effects . . . . . . . . . . . . . . . . . . . . 34 2.1.3 The Lambertian+Specular Model . . . . . . . . . . . . . . . . 36 2.1.4 Area Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 2.2 Inference from Shading . . . . . . . . . . . . . . . . . . . . . . . . . . 37 2.2.1 Radiometric Calibration and High Dynamic Range Images . . 38 2.2.2 The Shape of Specularities . . . . . . . . . . . . . . . . . . . 40 2.2.3 Inferring Lightness and Illumination . . . . . . . . . . . . . . 43 2.2.4 Photometric Stereo: Shape from Multiple Shaded Images . . 46 2.3 Modelling Interreflection . . . . . . . . . . . . . . . . . . . . . . . . . 52 2.3.1 The Illumination at a Patch Due to an Area Source . . . . . 52 2.3.2 Radiosity and Exitance . . . . . . . . . . . . . . . . . . . . . 54 2.3.3 An Interreflection Model . . . . . . . . . . . . . . . . . . . . . 55 2.3.4 Qualitative Properties of Interreflections . . . . . . . . . . . . 56 2.4 Shape from One Shaded Image . . . . . . . . . . . . . . . . . . . . . 59 2.5 Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 3 Color 68 3.1 Human Color Perception . . . . . . . . . . . . . . . . . . . . . . . . . 68 3.1.1 Color Matching . . . . . . . . . . . . . . . . . . . . . . . . . . 68 3.1.2 Color Receptors . . . . . . . . . . . . . . . . . . . . . . . . . 71 3.2 The Physics of Color . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 3.2.1 The Color of Light Sources . . . . . . . . . . . . . . . . . . . 73 3.2.2 The Color of Surfaces . . . . . . . . . . . . . . . . . . . . . . 76 3.3 Representing Color . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 3.3.1 Linear Color Spaces . . . . . . . . . . . . . . . . . . . . . . . 77 3.3.2 Non-linear Color Spaces . . . . . . . . . . . . . . . . . . . . . 83 3.4 AModel of Image Color . . . . . . . . . . . . . . . . . . . . . . . . . 86 3.4.1 The Diffuse Term . . . . . . . . . . . . . . . . . . . . . . . . . 88 3.4.2 The Specular Term . . . . . . . . . . . . . . . . . . . . . . . . 90 3.5 Inference from Color . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 3.5.1 Finding Specularities Using Color . . . . . . . . . . . . . . . 90 3.5.2 Shadow Removal Using Color . . . . . . . . . . . . . . . . . . 92 3.5.3 Color Constancy: Surface Color from Image Color . . . . . . 95 3.6 Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 II EARLY VISION: JUST ONE IMAGE 105 4 Linear Filter

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Book SynopsisThis book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering. By only assuming a knowledge of calculus, the authors develop, in a rigorous yet down to earth manner, the mathematical theory behind concepts such as: vectors spaces, bases, linear maps, duality, Hermitian spaces, the spectral theorems, SVD, and the primary decomposition theorem. At all times, pertinent real-world applications are provided. This book includes the mathematical explanations for the tools used which we believe that is adequate for computer scientists, engineers and mathematicians who really want to do serious research and make significant contributions in their respective fields.

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Book SynopsisThis comprehensive compendium describes a parametric model and algorithmic theory to represent geometric entities with dependent uncertainties between them. The theory, named Linear Parametric Geometric Uncertainty Model (LPGUM), is an expressive and computationally efficient framework that allows to systematically study geometric uncertainty and its related algorithms in computer geometry.The self-contained monograph is of great scientific, technical, and economic importance as geometric uncertainty is ubiquitous in mechanical CAD/CAM, robotics, computer vision, wireless networks and many other fields. Geometric models, in contrast, are usually exact and do not account for these inaccuracies.This useful reference text benefits academics, researchers, and practitioners in computer science, robotics, mechanical engineering and related fields.

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Book SynopsisCognitive computing simulates human thought processes with self-learning algorithms that utilize data mining, pattern recognition, and natural language processing. The integration of deep learning improves the performance of Cognitive computing systems in many applications, helping in utilizing heterogeneous data sets and generating meaningful insights.

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Book SynopsisGet started in the rapidly expanding field of computer vision with this practical guide. Written by Adrian Kaehler and Gary Bradski, creator of the open source OpenCV library, this book provides a thorough introduction for developers, academics, roboticists, and hobbyists.

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Book SynopsisGenerative AI is the hottest topic in tech. This practical book teaches machine learning engineers and data scientists how to use TensorFlow and Keras to create impressive generative deep learning models from scratch

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Book SynopsisTable of Contents1. Vision, the Challenge2. Images and Imaging Operations3. Image Filtering and Morphology4. The Role of Thresholding5. Edge Detection6. Corner, Interest Point and Invariant Feature Detection7. Texture Analysis8. Binary Shape Analysis9. Boundary Pattern Analysis10. Line, Circle and Ellipse Detection11. The Generalised Hough Transform12. Object Segmentation and Shape Models13. Basic Classification Concepts14. Machine Learning: Probabilistic Methods15. Deep Learning Networks16. The Three-Dimensional World17. Tackling the Perspective n-point Problem18. Invariants and perspective19. Image transformations and camera calibration20. Motion21. Face Detection and Recognition: the Impact of Deep Learning22. Surveillance23. In-Vehicle Vision Systems24. Epilogue—Perspectives in VisionAppendix A: Robust statisticsAppendix B: The Sampling TheoremAppendix C: The representation of colourAppendix D: Sampling from distributions

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Book SynopsisIntroduction.- Fingerprint Recognition.- Face Recognition.- Iris Recognition.- Additional Biometric Traits.- Multibiometrics.- Security of Biometric Systems.Table of ContentsIntroduction.- Fingerprint Recognition.- Face Recognition.- Iris Recognition.- Additional Biometric Traits.- Multibiometrics.- Security of Biometric Systems.

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Book SynopsisOBJECT DETECTION BY STEREO VISION IMAGES Since both theoretical and practical aspects of the developments in this field of research are explored, including recent state-of-the-art technologies and research opportunities in the area of object detection, this book will act as a good reference for practitioners, students, and researchers. Current state-of-the-art technologies have opened up new opportunities in research in the areas of object detection and recognition of digital images and videos, robotics, neural networks, machine learning, stereo vision matching algorithms, soft computing, customer prediction, social media analysis, recommendation systems, and stereo vision. This book has been designed to provide directions for those interested in researching and developing intelligent applications to detect an object and estimate depth. In addition to focusing on the performance of the system using high-performance computing techniques, a technical overview of certain tools, languages,Table of ContentsPreface xiii 1 Data Conditioning for Medical Imaging 1 Shahzia Sayyad, Deepti Nikumbh, Dhruvi Lalit Jain, Prachi Dhiren Khatri, Alok Saratchandra Panda and Rupesh Ravindra Joshi 1.1 Introduction 2 1.2 Importance of Image Preprocessing 2 1.3 Introduction to Digital Medical Imaging 3 1.3.1 Types of Medical Images for Screening 4 1.3.1.1 X-rays 4 1.3.1.2 Computed Tomography (CT) Scan 4 1.3.1.3 Ultrasound 4 1.3.1.4 Magnetic Resonance Imaging (MRI) 5 1.3.1.5 Positron Emission Tomography (PET) Scan 5 1.3.1.6 Mammogram 5 1.3.1.7 Fluoroscopy 5 1.3.1.8 Infrared Thermography 6 1.4 Preprocessing Techniques of Medical Imaging Using Python 6 1.4.1 Medical Image Preprocessing 6 1.4.1.1 Reading the Image 7 1.4.1.2 Resizing the Image 7 1.4.1.3 Noise Removal 8 1.4.1.4 Filtering and Smoothing 9 1.4.1.5 Image Segmentation 11 1.5 Medical Image Processing Using Python 13 1.5.1 Medical Image Processing Methods 16 1.5.1.1 Image Formation 17 1.5.1.2 Image Enhancement 19 1.5.1.3 Image Analysis 19 1.5.1.4 Image Visualization 19 1.5.1.5 Image Management 19 1.6 Feature Extraction Using Python 20 1.7 Case Study on Throat Cancer 24 1.7.1 Introduction 24 1.7.1.1 HSI System 25 1.7.1.2 The Adaptive Deep Learning Method Proposed 25 1.7.2 Results and Findings 27 1.7.3 Discussion 28 1.7.4 Conclusion 29 1.8 Conclusion 29 References 30 Additional Reading 31 Key Terms and Definition 32 2 Detection of Pneumonia Using Machine Learning and Deep Learning Techniques: An Analytical Study 33 Shravani Nimbolkar, Anuradha Thakare, Subhradeep Mitra, Omkar Biranje and Anant Sutar 2.1 Introduction 33 2.2 Literature Review 35 2.3 Learning Methods 41 2.3.1 Machine Learning 41 2.3.2 Deep Learning 42 2.3.3 Transfer Learning 42 2.4 Detection of Lung Diseases Using Machine Learning and Deep Learning Techniques 43 2.4.1 Dataset Description 43 2.4.2 Evaluation Platform 44 2.4.3 Training Process 44 2.4.4 Model Evaluation of CNN Classifier 46 2.4.5 Mathematical Model 47 2.4.6 Parameter Optimization 47 2.4.7 Performance Metrics 50 2.5 Conclusion 52 References 53 3 Contamination Monitoring System Using IOT and GIS 57 Kavita R. Singh, Ravi Wasalwar, Ajit Dharmik and Deepshikha Tiwari 3.1 Introduction 58 3.2 Literature Survey 58 3.3 Proposed Work 60 3.4 Experimentation and Results 61 3.4.1 Experimental Setup 61 3.5 Results 64 3.6 Conclusion 70 Acknowledgement 71 References 71 4 Video Error Concealment Using Particle Swarm Optimization 73 Rajani P. K. and Arti Khaparde 4.1 Introduction 74 4.2 Proposed Research Work Overview 75 4.3 Error Detection 75 4.4 Frame Replacement Video Error Concealment Algorithm 77 4.5 Research Methodology 77 4.5.1 Particle Swarm Optimization 78 4.5.2 Spatio-Temporal Video Error Concealment Method 78 4.5.3 Proposed Modified Particle Swarm Optimization Algorithm 79 4.6 Results and Analysis 83 4.6.1 Single Frame With Block Error Analysis 85 4.6.2 Single Frame With Random Error Analysis 86 4.6.3 Multiple Frame Error Analysis 88 4.6.4 Sequential Frame Error Analysis 91 4.6.5 Subjective Video Quality Analysis for Color Videos 93 4.6.6 Scene Change of Videos 94 4.7 Conclusion 95 4.8 Future Scope 97 References 97 5 Enhanced Image Fusion with Guided Filters 99 Nalini Jagtap and Sudeep D. Thepade 5.1 Introduction 100 5.2 Related Works 100 5.3 Proposed Methodology 102 5.3.1 System Model 102 5.3.2 Steps of the Proposed Methodology 104 5.4 Experimental Results 104 5.4.1 Entropy 104 5.4.2 Peak Signal-to-Noise Ratio 105 5.4.3 Root Mean Square Error 107 5.4.3.1 Qab/f 108 5.5 Conclusion 108 References 109 6 Deepfake Detection Using LSTM-Based Neural Network 111 Tejaswini Yesugade, Shrikant Kokate, Sarjana Patil, Ritik Varma and Sejal Pawar 6.1 Introduction 111 6.2 Related Work 112 6.2.1 Deepfake Generation 112 6.2.2 LSTM and CNN 112 6.3 Existing System 113 6.3.1 AI-Generated Fake Face Videos by Detecting Eye Blinking 113 6.3.2 Detection Using Inconsistence in Head Pose 113 6.3.3 Exploiting Visual Artifacts 113 6.4 Proposed System 114 6.4.1 Dataset 114 6.4.2 Preprocessing 114 6.4.3 Model 115 6.5 Results 117 6.6 Limitations 119 6.7 Application 119 6.8 Conclusion 119 References 119 7 Classification of Fetal Brain Abnormalities with MRI Images: A Survey 121 Kavita Shinde and Anuradha Thakare 7.1 Introduction 121 7.2 Related Work 123 7.3 Evaluation of Related Research 129 7.4 General Framework for Fetal Brain Abnormality Classification 129 7.4.1 Image Acquisition 130 7.4.2 Image Pre-Processing 130 7.4.2.1 Image Thresholding 130 7.4.2.2 Morphological Operations 131 7.4.2.3 Hole Filling and Mask Generation 131 7.4.2.4 MRI Segmentation for Fetal Brain Extraction 132 7.4.3 Feature Extraction 132 7.4.3.1 Gray-Level Co-Occurrence Matrix 133 7.4.3.2 Discrete Wavelet Transformation 133 7.4.3.3 Gabor Filters 134 7.4.3.4 Discrete Statistical Descriptive Features 134 7.4.4 Feature Reduction 134 7.4.4.1 Principal Component Analysis 135 7.4.4.2 Linear Discriminant Analysis 136 7.4.4.3 Non-Linear Dimensionality Reduction Techniques 137 7.4.5 Classification by Using Machine Learning Classifiers 137 7.4.5.1 Support Vector Machine 138 7.4.5.2 K-Nearest Neighbors 138 7.4.5.3 Random Forest 139 7.4.5.4 Linear Discriminant Analysis 139 7.4.5.5 Naïve Bayes 139 7.4.5.6 Decision Tree (DT) 140 7.4.5.7 Convolutional Neural Network 140 7.5 Performance Metrics for Research in Fetal Brain Analysis 141 7.6 Challenges 142 7.7 Conclusion and Future Works 142 References 143 8 Analysis of COVID-19 Data Using Machine Learning Algorithm 147 Chinnaiah Kotadi, Mithun Chakravarthi K., Srihari Chintha and Kapil Gupta 8.1 Introduction 147 8.2 Pre-Processing 148 8.3 Selecting Features 149 8.4 Analysis of COVID-19–Confirmed Cases in India 152 8.4.1 Analysis to Highest COVID-19–Confirmed Case States in India 153 8.4.2 Analysis to Highest COVID-19 Death Rate States in India 153 8.4.3 Analysis to Highest COVID-19 Cured Case States in India 154 8.4.4 Analysis of Daily COVID-19 Cases in Maharashtra State 155 8.5 Linear Regression Used for Predicting Daily Wise COVID- 19 Cases in Maharashtra 156 8.6 Conclusion 157 References 157 9 Intelligent Recommendation System to Evaluate Teaching Faculty Performance Using Adaptive Collaborative Filtering 159 Manish Sharma and Rutuja Deshmukh 9.1 Introduction 160 9.2 Related Work 162 9.3 Recommender Systems and Collaborative Filtering 164 9.4 Proposed Methodology 165 9.5 Experiment Analysis 167 9.6 Conclusion 168 References 168 10 Virtual Moratorium System 171 Manisha Bhende, Muzasarali Badger, Pranish Kumbhar, Vedanti Bhatkar and Payal Chavan 10.1 Introduction 172 10.1.1 Objectives 172 10.2 Literature Survey 172 10.2.1 Virtual Assistant—BLU 172 10.2.2 HDFC Ask EVA 173 10.3 Methodologies of Problem Solving 173 10.4 Modules 174 10.4.1 Chatbot 174 10.4.2 Android Application 175 10.4.3 Web Application 175 10.5 Detailed Flow of Proposed Work 176 10.5.1 System Architecture 176 10.5.2 DFD Level 1 177 10.6 Architecture Design 178 10.6.1 Main Server 178 10.6.2 Chatbot 178 10.6.3 Database Architecture 180 10.6.4 Web Scraper 180 10.7 Algorithms Used 181 10.7.1 AES-256 Algorithm 181 10.7.2 Rasa NLU 181 10.8 Results 182 10.9 Discussions 183 10.9.1 Applications 183 10.9.2 Future Work 183 10.9.3 Conclusion 183 References 183 11 Efficient Land Cover Classification for Urban Planning 185 Vandana Tulshidas Chavan and Sanjeev J. Wagh 11.1 Introduction 185 11.2 Literature Survey 189 11.3 Proposed Methodology 191 11.4 Conclusion 192 References 192 12 Data-Driven Approches for Fake News Detection on Social Media Platforms: Review 195 Pradnya Patil and Sanjeev J. Wagh 12.1 Introduction 196 12.2 Literature Survey 196 12.3 Problem Statement and Objectives 201 12.3.1 Problem Statement 201 12.3.2 Objectives 201 12.4 Proposed Methodology 202 12.4.1 Pre-Processing 202 12.4.2 Feature Extraction 203 12.4.3 Classification 203 12.5 Conclusion 204 References 204 13 Distance Measurement for Object Detection for Automotive Applications Using 3D Density-Based Clustering 207 Anupama Patil, Manisha Bhende, Suvarna Patil and P. P. Shevatekar 13.1 Introduction 208 13.2 Related Work 210 13.3 Distance Measurement Using Stereo Vision 213 13.3.1 Calibration of the Camera 215 13.3.2 Stereo Image Rectification 215 13.3.3 Disparity Estimation and Stereo Matching 216 13.3.4 Measurement of Distance 217 13.4 Object Segmentation in Depth Map 218 13.4.1 Formation of Depth Map 218 13.4.2 Density-Based in 3D Object Grouping Clustering 218 13.4.3 Layered Images Object Segmentation 219 13.4.3.1 Image Layer Formation 221 13.4.3.2 Determination of Object Boundaries 222 13.5 Conclusion 223 References 224 14 Real-Time Depth Estimation Using BLOB Detection/ Contour Detection 227 Arokia Priya Charles, Anupama V. Patil and Sunil Dambhare 14.1 Introduction 227 14.2 Estimation of Depth Using Blob Detection 229 14.2.1 Grayscale Conversion 230 14.2.2 Thresholding 231 14.2.3 Image Subtraction in Case of Input with Background 232 14.2.3.1 Preliminaries 233 14.2.3.2 Computing Time 234 14.3 Blob 234 14.3.1 BLOB Extraction 234 14.3.2 Blob Classification 235 14.3.2.1 Image Moments 236 14.3.2.2 Centroid Using Image Moments 238 14.3.2.3 Central Moments 238 14.4 Challenges 241 14.5 Experimental Results 241 14.6 Conclusion 251 References 255 Index 257

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Book SynopsisThe six volume set of LNCS 12622-12627 constitutes the proceedings of the 15th Asian Conference on Computer Vision, ACCV 2020, held in Kyoto, Japan, in November/ December 2020.*The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics: Part I: 3D computer vision; segmentation and grouping Part II: low-level vision, image processing; motion and tracking Part III: recognition and detection; optimization, statistical methods, and learning; robot vision Part IV: deep learning for computer vision, generative models for computer vision Part V: face, pose, action, and gesture; video analysis and event recognition; biomedical image analysis Part VI: applications of computer vision; vision for X; datasets and performance analysis *The conference was held virtually.Table of ContentsApplications of Computer Vision, Vision for X.- Query by Strings and Return Ranking Word Regions with Only One Look.- Single-Image Camera Response Function Using Prediction Consistency and Gradual Refinement.- FootNet: An efficient convolutional network for multiview 3D foot reconstruction.- Synthetic-to-real domain adaptation for lane detection.- RAF-AU Database: In-the-Wild Facial Expressions with Subjective Emotion Judgement and Objective AU Annotations.- DoFNet: Depth of Field Difference Learning for Detecting Image Forgery.- Explaining image classifiers by removing input features using generative models.- Do We Need Sound for Sound Source Localization?.- Modular Graph Attention Network for Complex Visual Relational Reasoning.- CloTH-VTON: Clothing Three-dimensional reconstruction for Hybrid image-based Virtual Try-ON.- Multi-label X-ray Imagery Classification via Bottom-up Attention and Meta Fusion.- Learning End-to-End Action Interaction by Paired-Embedding Data Augmentation.- Sketch-to-Art: Synthesizing Stylized Art Images From Sketches.- Road Obstacle Detection Method Based on an Autoencoder with Semantic Segmentation.- SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection.- Trainable Structure Tensors for Autonomous Baggage Threat Detection Under Extreme Occlusion.- Audiovisual Transformer with Instance Attention for Audio-Visual Event Localization.- Watch, read and lookup: learning to spot signs from multiple supervisors.- Domain-transferred Face Augmentation Network.- Pose Correction Algorithm for Relative Frames between Keyframes in SLAM.- Dense-Scale Feature Learning in Person Re-Identification.- Class-incremental Learning with Rectified Feature-Graph Preservation.- Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation.- Towards Robust Fine-grained Recognition by Maximal Separation of Discriminative Features.- Visually Guided Sound Source Separation using Cascaded Opponent Filter Network.- Channel Recurrent Attention Networks for Video Pedestrian Retrieval.- In Defense of LSTMs for Addressing Multiple Instance Learning Problems.- Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score.- Show, Conceive and Tell: Image Captioning with Prospective Linguistic Information.- Datasets and Performance Analysis.- RGB-T Crowd Counting from Drone: A Benchmark and MMCCN Network.- Webly Supervised Semantic Embeddings for Large Scale Zero-Shot Learning.- Compensating for the Lack of Extra Training Data by Learning Extra Representation.- Class-Wise Difficulty-Balanced Loss for Solving Class-Imbalance.- OpenTraj: Assessing Prediction Complexity in Human Trajectories Datasets.- Pre-training without Natural Images.- TTPLA: An Aerial-Image Dataset for Detection and Segmentation of Transmission Towers and Power Lines.- A Day on Campus - An Anomaly Detection Dataset for Events in a Single Camera.- A Benchmark and Baseline for Language-Driven Image Editing.- Self-supervised Learning of Orc-Bert Augmentator for Recognizing Few-Shot Oracle Characters.- Understanding Motion in Sign Language: A New Structured Translation Dataset.- FreezeNet: Full Performance by Reduced Storage Costs.

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This book offers an overview of traditional big visual data analysis approaches and provides state-of-the-art solutions for several scene comprehension problems, indoor/outdoor classification, outdoor scene classification, and outdoor scene layout estimation. It is illustrated with numerous natural and synthetic color images, and extensive statistical analysis is provided to help readers visualize big visual data distribution and the associated problems. Although there has been some research on big visual data analysis, little work has been published on big image data distribution analysis using the modern statistical approach described in this book. By presenting a complete methodology on big visual data analysis with three illustrative scene comprehension problems, it provides a generic framework that can be applied to other big visual data analysis tasks.Table of ContentsIntroduction.- Scene Understanding Datasets.- Indoor/Outdoor classification with Multiple Experts.- Outdoor Scene Classification Using Labeled Segments.- Global-Attributes Assisted Outdoor Scene Geometric Labeling.- Conclusion and Future Work.

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Book SynopsisTable of Contents1. Programming in Python 2. Machine Learning Basics 3. Regression 4. Classification 5. Dimensionality reduction 6. Clustering 7. Ensemble methods 8. Feature extraction and selection 9. Introduction to Deep Learning 10. Neural Networks 11. Convolutional Neural Networks

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Book SynopsisMachine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing. There is a need for research that seeks to understand the development and efficiency of current methods that enable machines to see.Challenges and Applications for Implementing Machine Learning in Computer Vision is a collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. Highlighting a wide range of topics such as video segmentation, object recognition, and 3D modelling, this publication is ideally designed for computer scientists, medical professionals, computer engineers, information technology practitioners, industry experts, scholars, researchers, and students seeking current research on the utilization of evolving computer vision techniques.

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Book SynopsisThis two-volume set LNCS 11574 and 11575 constitutes the refereed proceedings of the 11th International Conference on Virtual, Augmented and Mixed Reality, VAMR 2019, held in July 2019 as part of HCI International 2019 in Orlando, FL, USA. HCII 2019 received a total of 5029 submissions, of which 1275 papers and 209 posters were accepted for publication after a careful reviewing process. The 80 papers presented in this volume were organized in topical sections named: multimodal interaction in VR, rendering, layout, visualization and navigation, avatars, embodiment and empathy in VAMR, cognitive and health issues in VAMR, VAMR and robots, VAMR in learning, training and entertainment, VAMR in aviation, industry and the military.Table of ContentsMultimodal interaction in VR.- rendering, layout, visualization and navigation.- avatars, embodiment and empathy in VAMR.- cognitive and health issues in VAMR.- VAMR and robots.- VAMR in learning, training and entertainment.- VAMR in aviation, industry and the military.

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Book SynopsisThis book discusses the computational geometry, topology and physics of digital images and video frame sequences. This trio of computational approaches encompasses the study of shape complexes, optical vortex nerves and proximities embedded in triangulated video frames and single images, while computational geometry focuses on the geometric structures that infuse triangulated visual scenes. The book first addresses the topology of cellular complexes to provide a basis for an introductory study of the computational topology of visual scenes, exploring the fabric, shapes and structures typically found in visual scenes. The book then examines the inherent geometry and topology of visual scenes, and the fine structure of light and light caustics of visual scenes, which bring into play catastrophe theory and the appearance of light caustic folds and cusps. Following on from this, the book introduces optical vortex nerves in triangulated digital images. In this context, computational physics is synonymous with the study of the fine structure of light choreographed in video frames. This choreography appears as a sequence of snapshots of light reflected and refracted from surface shapes, providing a solid foundation for detecting, analyzing and classifying visual scene shapes.Trade Review“The book is presented in a very accessible fashion. … The book is suitable for graduate students and researchers interested in computational geometry and computer vision. Moreover, it can be used as a professional reference.” (Krzysztof Gdawiec, zbMATH 1437.68005, 2020)Table of ContentsComputational Geometry, Topology and Physics of Visual Scenes.- Cell Complexes, Filaments, Vortexes and Shapes Within a Shape.- Shape Fingerprints, Geodesic Trails and Free Abelian Groups on Skeletal Vortexes.- What Nerve Complexes Tell Us About Image Shapes.

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Book SynopsisThis book constitutes the refereed proceedings of the 25th International Conference, CRIWG+CollabTech 2019, held in Kyoto, Japan in September 2019. The 12 full papers presented in this book together with 8 work-in-progress papers were carefully reviewed and selected from 28 submissions, and the program also included an invited talk. This year presented a merger of the CRIWG and CollabTech conferences after having been jointly held since 2014. The papers published in this proceedings focus on innovative collaboration technologies and social computing.Table of ContentsAwareness of Complementary Knowledge in CSCL: Impact on Learners’ Knowledge Exchange in Small Groups.- Identifying Socio-Technical Means to Support Small Loosely Coupled Groups of Volunteers.- The analysis of collaborative science learning with simulations through dual eye-tracking techniques.- Hybrid Meetings in the Modern Workplace: Stories of Success and Failure.- A CSCL script for supporting moral reasoning in the ethics classroom.- Tailorable Remote Assistance with RemoteAssistKit: A Study of and Design Response to Remote Assistance in the Manufacturing Industry.- Vision-Based Indoor Positioning (VBIP) - An Indoor AR Navigation System With A Virtual Tour Guide.- Developing Hyper-stories in the Context of Cultural Heritage Appreciation.- A Method for Automated Detection of Cultural Difference.- FootstepsMixer: a Tool to Express Multiple People’s Footsteps in a Footstep Transmission System for Awareness Support.- Speech Speed Awareness System Slows Down Native Speaker’s Talk.- A Comic-style Chat System with Japanese Expression Techniques for More Expressive Communication.- Modeling of non-verbal behaviors of students in cooperative learning by using OpenPose.- Implementing a Serious Game to Improve Communication and Social Skills for Children with Autism.- DiAna-AD: Dialog Analysis for Adjusting Duration during Face-to-face Collaborative Discussion.- Group Dynamics in Gameful Collaborative Innovation Processes.- Discovering Latent Country Words: A Step towards Cross-cultural Emotional Communication.- Evaluation of a campus navigation application using an AR character guide.- An Automated Structural Approach to Support Theatrical Performances by Introducing Gesture Recognition to a Cuing System.- Proposal of Emphasized Pseudo Expression for Improving the Recognition of the Presence and Contribution of Remote Participants in Cooperative Work.

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Book SynopsisThe two-volume set LNCS 11751 and 11752 constitutes the refereed proceedings of the 20th International Conference on Image Analysis and Processing, ICIAP 2019, held in Trento, Italy, in September 2019. The 117 papers presented were carefully reviewed and selected from 207 submissions. The papers cover both classic and the most recent trends in image processing, computer vision, and pattern recognition, addressing both theoretical and applicative aspects. They are organized in the following topical sections: Video Analysis and Understanding; Pattern Recognition and Machine Learning; Deep Learning; Multiview Geometry and 3D Computer Vision; Image Analysis, Detection and Recognition; Multimedia; Biomedical and Assistive Technology; Digital Forensics; Image processing for Cultural Heritage.Table of ContentsVideo Analysis and Understanding.- Pattern Recognition and Machine Learning.- Deep Learning.- Multiview Geometry and 3D Computer Vision.- Image Analysis, Detection and Recognition.- Multimedia.- Biomedical and Assistive Technology.- Digital Forensics.- Image processing for Cultural Heritage.

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Book SynopsisThe two volumes LNCS 11935 and 11936 constitute the proceedings of the 9th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2019, held in Nanjing, China, in October 2019. The 84 full papers presented were carefully reviewed and selected from 252 submissions.The papers are organized in two parts: visual data engineering; and big data and machine learning. They cover a large range of topics including information theoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics, bioinformatics, computational biology and brain-computer interfaces, as well as advances in fundamental pattern recognition techniques relevant to image processing, computer vision and machine learning.

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Book SynopsisThis book addresses one of the most important unsolved problems in artificial intelligence: the task of learning, in an unsupervised manner, from massive quantities of spatiotemporal visual data that are available at low cost. The book covers important scientific discoveries and findings, with a focus on the latest advances in the field. Presenting a coherent structure, the book logically connects novel mathematical formulations and efficient computational solutions for a range of unsupervised learning tasks, including visual feature matching, learning and classification, object discovery, and semantic segmentation in video. The final part of the book proposes a general strategy for visual learning over several generations of student-teacher neural networks, along with a unique view on the future of unsupervised learning in real-world contexts. Offering a fresh approach to this difficult problem, several efficient, state-of-the-art unsupervised learning algorithms are reviewed in detail, complete with an analysis of their performance on various tasks, datasets, and experimental setups. By highlighting the interconnections between these methods, many seemingly diverse problems are elegantly brought together in a unified way. Serving as an invaluable guide to the computational tools and algorithms required to tackle the exciting challenges in the field, this book is a must-read for graduate students seeking a greater understanding of unsupervised learning, as well as researchers in computer vision, machine learning, robotics, and related disciplines. Table of Contents1. Unsupervised Visual Learning: from Pixels to Seeing.- 2. Unsupervised Learning of Graph and Hypergraph Matching.- 3. Unsupervised Learning of Graph and Hypergraph Clustering.- 4. Feature Selection meets Unsupervised Learning.- 5. Unsupervised Learning of Object Segmentation in Video with Highly Probable Positive Features.- 6. Coupling Appearance and Motion: Unsupervised Clustering for Object Segmentation through Space and Time.- 7. Unsupervised Learning in Space and Time over Several Generations of Teacher and Student Networks.- 8. Unsupervised Learning Towards the Future.

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Book SynopsisThis book constitutes the post-conference proceedings of the First International Conference on Emerging Technologies and the Digital Transformation of Museums and Heritage Sites, RISE IMET 2020, held in Nicosia, Cyprus, in June 2021*.The 23 revised full papers were carefully reviewed and selected from 38 submissions. The papers are organized in the following topical sections: digital curation and visitor engagement in museums and heritage sites; VR, AR, MR, mobile applications and gamification in museums and heritage sites; digital storytelling and embodied characters for the interpretation of cultural heritage; emerging technologies, difficult heritage and affective practices; participatory approaches, crowdsourcing and new technologies; digitization, documentation and digital representation of cultural heritage.* The conference was held virtually due to the COVID-19 pandemic.Table of ContentsDigital curation and visitor engagement in museums and heritage sites.- VR, AR, MR, mobile applications and gamification in museums and heritage sites.- Digital storytelling and embodied characters for the interpretation of cultural heritage.- Emerging technologies, difficult heritage and affective practices.- Participatory approaches, crowdsourcing and new technologies.- Digitization, documentation and digital representation of cultural heritage.

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Book SynopsisThis book constitutes the refereed proceedings of the 13th International Conference on Computer Vision Systems, ICVS 2021, held in September 2021. Due to COVID-19 pandemic the conference was held virtually. The 20 papers presented were carefully reviewed and selected from 29 submissions. cover a broad spectrum of issues falling under the wider scope of computer vision in real-world applications, including among others, vision systems for robotics, autonomous vehicles, agriculture and medicine. In this volume, the papers are organized into the sections: attention systems; classification and detection; semantic interpretation; video and motion analysis; computer vision systems in agriculture.Table of ContentsAttention Systems.- Thermal Image Super-Resolution Using Second-Order Channel Attention with Varying Receptive Fields.- MARL: Multimodal Attentional Representation Learning for Disease Prediction.- Object Localization with Attribute Preference based on Top-Down Attention.- See the silence: improving visual-only voice activity detection by optical flow and RGB fusion.- Classification and Detection.- Score to Learn: a Comparative Analysis of Scoring Functions for Active Learning in Robotics.- Enhancing the performance of image classification through features automatically learned from depth-maps.- Object Detection on TPU Accelerated Embedded Devices.- Tackling Inter-Class Similarity and Intra-Class Variance for Microscopic Image-based Classification.- Semantic Interpretation.- Measuring the Sim2Real gap in 3D Object classification for different 3D data representation.- Spatially-Constrained Semantic Segmentation with Topological Μaps and Visual Εmbeddings.- Knowledge-enabled generation of semantically annotated image sequences of manipulation activities from VR demonstrations.- Make It Easier: An Empirical Simplification of a Deep 3D Segmentation Network for Human Body Parts.- Video and Motion Analysis.- Video Popularity Prediction through Fusing Early Viewership with Video Content.- Action Prediction during Human-Object Interaction based on DTW and Early Fusion of Human and Object Representations.- GridTrack: Detection and Tracking of Multiple Objects in Dynamic Occupancy Grids.- An Efficient Video Desnowing and Deraining Method with a Novel Variant Dataset.- Computer Vision Systems in Agriculture.- Robust Counting of Soft Fruit through Occlusions with Re-identification.- Non-destructive Soft Fruit Mass and Volume Estimation for Phenotyping in Horticulture.- Learning Image-based Contaminant Detection in Wool Fleece from Noisy Annotations.- Active Learning for Crop-Weed Discrimination by Image Classification from Convolutional Neural Network’s Feature Pyramid Levels.

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Book SynopsisThe two volume set LNCS 13052 and 13053 constitutes the refereed proceedings of the 19th International Conference on Computer Analysis of Images and Patterns, CAIP 2021, held virtually, in September 2021. The 87 papers presented were carefully reviewed and selected from 129 submissions. The papers are organized in the following topical sections across the 2 volumes: 3D vision, biomedical image and pattern analysis; machine learning; feature extractions; object recognition; face and gesture, guess the age contest, biometrics, cryptography and security; and segmentation and image restoration.Table of Contents3D Vision.- Simultaneous Bi-Directional Structured Light Encoding for Practical Uncalibrated Profilometry.- Joint Global ICP for Improved Automatic Alignment of Full Turn Object Scans.- Fast Projector-Driven Structured Light Matching in Sub-Pixel Accuracy using Bilinear Interpolation Assumption.- Pyramidal Layered Scene Inference with Image Outpainting for Monocular View Synthesis.- Out of the Box: Embodied Navigation in the Real World.-Toward a novel LSB-based collusion-secure fingerprinting schema for 3D video.- A Combinatorial Coordinate System for the Vertices in the Octagonal C4C8 ( R) Grid.- Bilingual Speech Recognition by Estimating Speaker Geometry from Video Data.- Cost-efficient Color Correction Approach on Uncontrolled Lighting Conditions.- HPA-Net: Hierarchical and Parallel Aggregation Network for Context Learning in Stereo Matching.- MTStereo 2.0: accurate stereo depth estimation via Max-tree matching.- Biomedical Image and Pattern Analysis.- H-OCS: a hybrid optic cup segmentation of retinal images.- Retinal Vessel Segmentation using Blending-based Conditional Generative Adversarial Networks.- U-shaped densely connected Convolutions for Left ventricle segmentation from CMR images.- Deep Learning approaches for Head and Operculum Segmentation in Zebrafish Microscopy Images.- Shape Analysis Approach towards Assessment of Cleft Lip Repair Outcome.- MMEC: Multi-Modal Ensemble Classifier for Protein Secondary Structure Prediction.- Breast Cancer Brain Metastasis: Automated MRI Image Analysis for the Prediction of Primary Cancer Using Radiomics.- An Adaptive Semi-Automated Integrated System for Multiple Sclerosis Lesion Segmentation in Longitudinal MRI Scans Based on a Convolutional Neural Network.- A Three-Dimensional Reconstruction Integrated System for Brain Multiple Sclerosis Lesions.- Rule Extraction in the Assessment of Brain MRI Lesions in Multiple Sclerosis: Preliminary Findings.- Invariant Moments, Textural and Deep features for Diagnostic MR and CT Image Retrieval.- Toward multiwavelet Haar-Schauder entropy for biomedical signal reconstruction.- Machine Learning.- Handling Missing Observations with an RNN-based Prediction-Update Cycle.- eGAN: Unsupervised approach to class imbalance using transfer learning.- Progressive Contextual Excitation for Smart Farming Application.- Fine-Grained Image Classification for Pollen Grain Microscope Images.- Adaptive Style Transfer Using SISR.- Object-Centric Anomaly Detection using Memory Augmentation.- Document Language Classification: Hierarchical Model With Deep Learning Approach.- Parsing Digitized Vietnamese Paper Documents.- EnGraf-Net: Multiple Granularity Branch Network with Fine-Coarse Graft Grained for Classification Task.- When Deep Learners Change Their Mind: Learning Dynamics for Active Learning.- Learning to Navigate in the Gaussian Mixture Surface.- A Deep Hybrid Approach For Hate Speech Analysis.- On improving generalization of CNN-based image classification with delineation maps using the CORF push-pull inhibition operator.- Fast Hand Detection in Collaborative Learning Environments.- Assessing the Role of Boundary-level Objectives in Indoor Semantic Segmentation.- Skin lesion classification using convolutional neural networks based on Multi-Features Extraction.- Recursively Refined R-CNN: Instance Segmentation with Self-RoI Rebalancing.- Layer-wise Relevance Propagation based Sample Condensation for Kernel Machines.-

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Book SynopsisThis book, geared towards both students and professionals, examines the synthesis of artificial intelligence (AI) and psychology in detecting mis-/disinformation in digital media content, and suggests practical means to intervene and curtail this current global ‘infodemic’. This interdisciplinary book explores technological, psychological, philosophical, and linguistic insights into the nature of truth and deception, trust and credibility, cognitive biases and logical fallacies and how, through AI and human intervention, content users can be alerted to the presence of deception. The author investigates how AI can mimic the procedures and know-hows of humans, showing how AI can help spot fakes and how AI tools can work to debunk rumors and fact-check. The book describes how AI detection systems work and how they fit with broader societal and individual concerns. Each chapter focuses attention on key concepts and their inter-connection. The first part of the book seeks theoretical footing to understand our interactions with new information and reviews relevant empirical findings in behavioral sciences. The second part is about applied knowledge. The author looks at several known practices that guard us against deception, and provides several real-world examples of manipulative persuasive techniques in advertising, political propaganda, and public relations. She provides links to the downloadable executable files to three AI applications (clickbait, satire, and falsehood detectors) via LiT.RL GitHub, an open access repository. The book is useful to students and professionals studying AI and media studies as well as library and information professionals. Examines how artificial intelligence (AI) and psychology can aid in detecting mis-/disinformation and the language of deceit in digital media content; Suggests practical computational means to intervene and curtail the global ‘infodemic’ of fake news; Presents how AI can sift, sort, and shuffle digital content, to reduce the amount of content needed to be reviewed by humans. Table of ContentsIntroduction.- Infodemic in the Digital Media Content.- Part I. Human Nature of Deception and Perceptions of Truth.- Psychology of Mis-/Disinformation and Language of Deceit.- Library and Information Science on Credibility and Trust in Computing.- Philosophies of Truth.- Part II. Applied Practices and Artificial Intelligence (AI).- Investigation in Law Enforcement, Journalism, and Sciences.- Manipulation in Marketing, Advertising, and Public Relations.- Artificially Intelligent Solutions: Detection, Debunking, Fact-Checking.- Lessons for Infodemic Control and Future of Digital Content Verification.- Conclusion.

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Book SynopsisThe proceedings set LNCS 13231, 13232, and 13233 constitutes the refereed proceedings of the 21st International Conference on Image Analysis and Processing, ICIAP 2022, which was held during May 23-27, 2022, in Lecce, Italy,The 168 papers included in the proceedings were carefully reviewed and selected from 307 submissions. They deal with video analysis and understanding; pattern recognition and machine learning; deep learning; multi-view geometry and 3D computer vision; image analysis, detection and recognition; multimedia; biomedical and assistive technology; digital forensics and biometrics; image processing for cultural heritage; robot vision; etc. Table of ContentsPattern Recognition and Machine Learning.- Video Analysis & Understanding.- Special Session.

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Book SynopsisThis book constitutes the refereed proceedings of the Third Latin American Workshop, LAWCN 2021, held in Sao Luis do Maranhao, Brazil, during December 8–10, 2021.The 13 full papers and 3 short papers included in this book were carefully reviewed and selected from 27 submissions. They were organized in topical sections as follows: Interdisciplinary applications of Artificial Intelligence (AI) and Machine Learning (ML); AI and ML applied to robotics; AI and ML applied to biomedical sciences; Health issues and computational neuroscience; Software and hardware implementations in neuroscience; and Neuroengineering – science and technology.Table of ContentsInterdisciplinary applications of Artificial Intelligence (AI) and Machine Learning (ML).- Semantic segmentation of the cultivated area of plantations with U-net.- Use and Interpretation of Item Response Theory applied to Machine Learning.- AI and ML applied to robotics.- Towards Loop Closure Detection for SLAM Applications using Bag of Visual Features: Experiments and Simulation.- Loss Function Regularisation on the Iterated Racing Procedure for Automatic Tuning of RatSLAM Parameters.- Controlling the UR3 robotic arm using a leap motion: a comparative study.- AI and ML applied to biomedical sciences.- Web service based epileptic seizure detection by applying machine learning techniques.- Health issues and computational neuroscience.- Machine Learning Search of Novel Selective NaV1.2 and NaV1.6 Inhibitors as Potential Treatment against Dravet Syndrome.- Implementation of intra and extracellular nonperiodic scale-free stimulation in silico for the NEURON simulator.- In silico investigation of the effects of distinct temporal patterns of electrical stimulation to the amygdala using a network of Izhikevich neurons.- Software and hardware implementations in neuroscience.- Brain connectivity measures in EEG-based biometry for epilepsy patients.- A multiplatform output stage for the development of current-fixed electrical stimulators applied to neural electrophysiology.- Neuroengineering – science and technology.- Physiological self-regulation using biofeedback training: from concept to clinical applicability.- Movement-Related Electroencephalography in Stroke Patients across a Brain-Computer Interface-based Intervention.- Electrophysiological Correlates of Freeze of Gait in Parkinson Disease: Increased STN-LFP Alpha Power and the Possible Role of Attentional Circuits.- Effect of hand dominance when decoding motor imagery grasping tasks within the same hand.- Kinematic responses as a control strategy to visual occlusion.

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Book SynopsisThis volume constitutes the papers of two workshops which were held in conjunctionwith the First International Conference on Robotics, Computer Vision and Intelligent Systems,ROBOVIS 2020, Virtual Event, in November 4-6, 2020 and Second International Conference on Robotics, Computer Vision and Intelligent Systems,ROBOVIS 2021, Virtual Event, in October 25-27, 2021.The 11 revised full papers presented in this book were carefully reviewed and selectedfrom 53 submissions.Table of ContentsMulti-sensorial Environment Perception in Urban Environment.- An Extended Visual Intelligence Scheme for Disassembly in Automated Recycling Routines.- Multi-agent Path Finding and Acting with Small Reflex-based Mobile Robots.- Design and Experimental Analysis of an Adaptive Cruise Control.- Human-likeness Indicator for Robot Posture Control and Balance.- Visual Guidance of an on-Orbit Free-floating Manipulator using a Mobile Camera.- Semantic Segmentation of Marine Species in an Unconstrained Underwater Environment.- Social Embodiment of Companion Robots in Smart Spaces: IoRT for Independent Living.- Rapid Structure from Motion Frame Selection for Markerless Monocular SLAM.- Detecting Tool Keypoints with Synthetic Training Data.- Generating Versatile Training Samples for UAV Trajectory Prediction.

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Book SynopsisThis book constitutes the refereed proceedings of the 12th International Conference on High-Performance Computing Systems and Technologies in Scientific Research, Automation of Control and Production, HPCST 2022, held in Barnaul, Russia, during May 20–21, 2022. The 23 full papers included in this book were carefully reviewed and selected from 116 submissions. They were organized in topical sections as follows: hardware for high-performance computing and signal processing; information technologies and computer simulation of physical phenomena; computing technologies in data analysis and decision making; and computing technologies in information security applications.Table of Contents​Hardware for High-Performance Computing and Signal Processing.- Hierarchical Encoder-Decoder Neural Network with Self-Attention for Single-Channel Speech Denoising.- Calculation of Activation Functions in FPGA-Based Neuroprocessors Using the Cordic Algorithm.- Frequency-Domain Generalized Phase Transform Method in Pipeline Leaks Locating.- Information Technologies and Computer Simulation of Physical Phenomena.- Inverse Problem Regularization of Parametric Identification of the Particle Temperature Distribution of Gas-Thermal Flow with Optimization of Its Solution.- Application of the Heterogeneous Multiscale Finite Element Method for Modelling the Compressibility of Porous Media.- Parallel Non-Conforming Finite Element Technique for Mathematical Simulation of Fluid Flow in Multiscale Porous Media.- Darcy Problem Solution in a Mixed Formulation for Geological Media of Various Structures.- Mathematical Modeling of the Electromagnetic Field from a Solenoidal Coil in the Frequency Domain.- Computing Technologies in Data Analysis and Decision Making.- Novel Planning Technique for ERP Systems Implementation Projects.- Development of an Automated Document Classification System with a Predefined Structure.- Ontology-Based Data Mining Platform for Diagnosing Sowing Quality of Wheat Seeds.- Algorithm for the Classification of Coronary Heart Disease Based on the Use of Symptom Complexes in the Cardiovascular Environment.- Business Process Designing of the Institutional Ranking System of Higher Education of the Kyrgyz Republic.- Evaluation of the Efficiency of the Vaccination against Chickenpox Based on the Results of Simulation Modeling.- Hierarchical Volume Mesh Model of Heterogeneous Media Based on Non-Destructive Imaging Data.- Modeling а Potential Plant Habitat by Ensemble Machine Learning.- Information and Computing Technologies in Automation and Control Science.- Adaptive Traffic Signal Control Based on a Macroscopic Model of the Transport Network.- Optimization and Robustization of Angular Motion Control of an Automatic Maneuverable Aerial Vehicle.- Synthesis of the Rational Analyzing Function for Feature Extraction of Signals from the Electrostatic Location System.- Application of Computer Numerical Control in Eddy-Current Study Methods.- Computing Technologies in Information Security Applications.- Open-Source Solution for Identification and Blocking of Anomalous BGP-4 Routing Information.- Simulation of DDoS Attacks on LTE and LoRaWAN Protocols in the NS-3 Network Simulator.- Transaction-Oriented Approach to the Design of Information Systems Based on Formal Grammar.

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Book SynopsisThis two-volume set (CCIS 1762-1763) constitutes the refereed proceedings of the 4th International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2022, held in Bhopal, India, in December 2022. The 64 papers presented in this two-volume set were thoroughly reviewed and selected from 399 submissions. The papers are organized according to the following topical sections: ​machine learning and computational intelligence; data sciences; image processing and computer vision; network and cyber security.Table of ContentsMachine Learning and Computational Intelligence.- Data Sciences.- Image Processing and Computer Vision.- Network and Cyber Security.

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Book SynopsisThis book constitutes the refereed proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2021, held as a virtual event, February 8–10, 2021.The 16 full papers presented in this volume were carefully reviewed and selected from 371 submissions. The purpose of VISIGRAPP is to bring together researchers and practitioners interested in both theoretical advances and applications of computer vision, computer graphics and information visualization. VISIGRAPP is composed of four co-located conferences, each specialized in at least one of the aforementioned main knowledge areas, namely GRAPP, IVAPP, HUCAPP and VISAPP. The contributions were organized in topical sections as follows: Computer Graphics Theory and Applications; Human Computer Interaction Theory and Applications; Information Visualization Theory and Applications; Computer Vision Theory and Applications.Table of Contents​Computer Graphics Theory and Applications.- Impact of Avatar Representation in a Virtual Reality-based Multi-user Tunnel Fire Simulator for Training Purposes.- Facade Layout Completion with Long Short-term Memory Networks.- Human Computer Interaction Theory and Applications.- Generating Haptic Sensations over Spherical Surface.- Effects of Emotion-Induction Words on Memory and Pupillary Reactions while Viewing Visual Stimuli with Audio Guide.- A Bimanual Flick-based Japanese Software Keyboard using Direct Kanji Input.- Comparison of Cardiac Activity and Subjective Measures during Virtual Reality and Real Aircraft Flight.- Information Visualization Theory and Applications.- Improving Self-supervised Dimensionality Reduction: Exploring Hyperparameters and Pseudo-labeling Strategies.- Visualization of Source Code Similarity using 2.5D Semantic Software Maps.- Revisiting Order-Preserving, Gap-Avoiding Rectangle Packing.- Exploratory Data Analysis of Population Level Smartphone-sensed Data.- Towards Interactive Geovisualization Authoring Toolkit for Industry Use Cases.- Computer Vision Theory and Applications.- Global-fiirst Training Strategy with Convolutional Neural Networks to Improve Scale Invariance.- Spline-based Dense Medial Descriptors for Image Simplification using Saliency Maps.- BS-GAENets: Brain-spatial Feature Learning Via a Graph Deep Autoencoder for Multi-modal Neuroimaging Analysis.- Enhancing Backlight and Spotlight Images by the Retinex-inspired Bilateral Filter SuPeR-B.- Rethinking RNN-based Video Object Segmentation.

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Book SynopsisThis book constitutes the refereed post-conference proceedings of the workshops held at the 16th Asian Conference on Computer Vision, ACCV 2022, which took place in Macao, China, in December 2022. The 25 papers included in this book were carefully reviewed and selected from 40 submissions. They have been organized in topical sections as follows: Learning with limited data for face analysis; adversarial machine learning towards advanced vision systems; computer vision for medical computing; machine learning and computing for visual semantic analysis; vision transformers theory and applications; and deep learning-based small object detection from images and videos.Table of ContentsLearning with Limited Data for Face Analysis.- FAPN: Face Alignment Propagation Network for Face Video Super-Resolution.- Micro-expression recognition using a shallow ConvLSTM-based network.- Adversarial Machine Learning towards Advanced Vision Systems.- ADVFilter: Adversarial Example Generated by Perturbing Optical Path.- Enhancing Federated Learning Robustness Through clustering Non-IID Features.- Towards Improving the Anti-attack Capability of the RangeNet++.- Computer Vision for Medical Computing.- Ensemble Model of Visual Transformer and CNN Helps BA Diagnosis for Doctors in Underdeveloped Areas.- Understanding Tumor Micro Environment using Graph theory.- Handling Domain Shift for Lesion Detection via Semi-Supervised Domain Adaptation.- Photorealistic Facial Wrinkles Removal.- Improving Segmentation of Breast Arterial Calcifications from Digital Mammography: Good Annotation Is All You Need.- Machine Learning and Computing for Visual Semantic Analysis.- Towards Scene Understanding for Autonomous Operations on Airport Aprons.- Lightweight Hyperspectral Image Reconstruction Network with Deep Feature Hallucination.- A Transformer-based Model for Preoperative Early Recurrence Prediction of Hepatocellular Carcinoma with Muti-p.- CaltechFN: Distorted and Partially Occluded Digits.- Temporal Extension Topology Learning for Video-based Person Re-Identification.- Deep RGB-driven Learning Network for Unsupervised Hyperspectral Image Super-resolution.- Gift from nature: Potential Energy Minimization for explainable dataset distillation.- Object Centric Point Sets Feature Learning with Matrix Decomposition.- Aerial Image Segmentation via Noise Dispelling and Content Distilling.- Vision Transformers Theory and Applications.- Temporal Cross-attention for Action Recognition.- Transformer Based Motion In-Betweening.- Convolutional point Transformer.- Cross-Attention Transformer for Video Interpolation.- Deep Learning-Based Small Object Detection from Images and Videos.- Evaluating and Bench-marking Object Detection Models for Traffic Sign and Traffic Light Datasets.- Exploring Spatial-temporal Instance Relationships In an Intermediate Domain For Image-to-video Object Detection.

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Book SynopsisResearchers, academicians and professionals expone in this book their research in the application of intelligent computing techniques to software engineering. As software systems are becoming larger and complex, software engineering tasks become increasingly costly and prone to errors. Evolutionary algorithms, machine learning approaches, meta-heuristic algorithms, and others techniques can help the effi ciency of software engineering.

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Book SynopsisThe book contains the proceedings of the 8th Eurographics Rendering Workshop, which took place from 16th to 18th June, 1997, in Saint Etienne, France. After a series of seven successful events the workshop is now well established as the major international forum in the field of rendering and illumination techniques. It brought together the experts of this field. Their recent research results are compiled in this proceedings together with many color images that demonstrate new ideas and techniques. This year we received a total of 63 submissions of which 28 were selected for the workshop after a period of careful reviewing and evaluation by the 27 mem­ bers of the international program committee. The quality of the submissions was again very high and, unfortunately, many interesting papers had to be rejected. In addition to regular papers the program also contains two invited lectures by Shenchang Eric Chen (Live Picture) and Per Christensen (Mental Images). The papers in this proceedings contain new research results in the areas of Finite-Element and Monte-Carlo illumination algorithms, image-based render­ ing, outdoor and natural illumination, error metrics, perception, texture and color handling, data acquisition for rendering, and efficient use of hardware. While some contributions report results from more efficient or elegant algo­ rithms, others pursue new and experimental approaches to find better solutions to the open problems in rendering.Table of ContentsPolyhedral Geometry and the Two-Plane Parameterization.- Image-based Rendering with Controllable Illumination.- View-based Rendering: Visualizing Real Objects from Scanned Range and Color Data.- Applying Shape from Lighting Variation to Bump Map Capture.- Interactive Common Illumination for Computer Augmented Reality.- An Error Metric for Monte Carlo Ray Tracing.- Selective Culling of Discontinuity Lines.- Reconstructing the Visual Field of Compound Eyes.- Interactive Rendering of Globally Illuminated Glossy Scenes.- Incremental Updates to Scenes Illuminated by Area Light Sources.- Progressive Previewing of Ray-Traced Images Using Image Plane Discontinuity Meshing.- An Adaptive Representation of Spectral Data for Reflectance Computations.- A Geometry Dependent Texture Generation Framework for Simulating Surface Imperfections.- Nailboards: A Rendering Primitive for Image Caching in Dynamic Scenes.- Filtered Local Shading in the Wavelet Domain.- An Empirical Comparison of Progressive and Wavelet Radiosity.- Hierarchical Radiosity on Curved Surfaces.- A Hierarchical Subdivision Algorithm for Stochastic Radiosity Methods.- Bidirectional Radiosity.- Hierarchical Visibility in Terrains.- Hierarchical Lighting Simulation for Outdoor Scenes.- Plane-Parallel Radiance Transport for Global Illumination in Vegetation.- Lighting Reconstruction Using Fast and Adaptive Density Estimation Techniques.- A Neuro-Evolutionary Unbiased Global Illumination Algorithm.- Improved Irradiance Computation by Importance Sampling.- Adaptive Sampling and Bias Estimation in Path Tracing.- Application of Rendering Techniques to Monte-Carlo Physical Simulation of Gas Diffusion.- Global Illumination Techniques for the Simulation of Participating Media.- Invited Talk: Global Illumination for Professional 3D Animation, Visualization, and Special Effects.- Color Section.

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Book SynopsisThis book contains the proceedings of the 11th Eurographics Workshop on Rendering, which took place from the 26th to the 28th of June, 2000, in Brno, Czech Republic. Over the past 10 years, the Workshop has become the premier forum dedicated to research in rendering. Much of the work in rendering now appearing in other conferences and journals builds on ideas originally presented at the Workshop. This year we received a total of 84 submissions. Bachpaper was carefully reviewed by two of the 25 international programme committee members, as weil as external reviewers, selected by the co-chairs from a pool of 121 individuals (The programme committee and external reviewers are listed following the contents pages). In this review process, all submissions and reviews were handled electronically, with the exception of videos submitted with a few of the papers (however, some mpeg movies were also sent electronically). The overall quality of the submissions was exceptionally high. Space and time constraints forced the committee to make some difficult decisions. In the end, 33 papers were accepted, and they appear here. Almost all papers are accompanied by color images, which appear at the end of the book. The papers treat the following varied topics: radiosity, ray tracing, methods for global illumination, visibility, reftectance, filtering, perception, hardware assisted methods, real time rendering, modeling for effi­ cient rendering and new image representations.Table of ContentsMeasuring Visual Shape using Computer Graphics Psychophysics (M. S. Langer, H. H. Bülthoff).- Metropolis Light Transport for Participating Media (Mark Pauly, Thomas Kollig, Alexander Keller).- Density Control for Photon Maps (Frank Suykens, Yves D. Willems).- Weighted Importance Sampling Techniques for Monte Carlo Radiosity (Philippe Bekaert , Mateu Sbert, Yves D. Willems).- Fast Global Illumination Including Specular Effects (Xavier Granier, George Drettakis, Bruce Walter).- Virtual Occluders: An efficient Intermediate PVS representation (Vladlen Koltun, Yiorgos Chrysanthou, Daniel Cohen-Or).- Visibility Preprocessing with Occluder Fusion for Urban Walkthroughs (Peter Wonka, Michael Wimmer, Dieter Schmalstieg).- Real-Time Rendering of Densely Populated Urban Environments (Franco Tecchia, Yiorgos Chrysanthou).- Guaranteed Occlusion and Visibility in Cluster Hierarchical Radiosity (Luc Leblanc, Pierre Poulin).- Parameterized Animation Compression (Ziyad S. Hakura, Jerome E. Lengyel, John M. Snyder).- Wavelet Warping (Iddo Drori, Dani Lischinski).- Artistic Multiprojection Rendering (Maneesh Agrawala, Denis Zorin, Tamara Munzner).- A Closed-Form Solution for the Irradiance due to Linearly-Varying Luminaires (Min Chen, James Arvo).- Exact Illumination in Polygonal Environments using Vertex Tracing (Michael M. Stark, Richard F. Reisenfield).- Wavelet Radiosity on Arbitrary Planar Surfaces (Nicolas Holzschuch, Francois Cuny , Laurent Alonso).- Hierarchical Instantiation for Radiosity (Cyril Soler, Francois Sillion).- Unified Approach to Prefiltered Environment Maps (Jan Kautz, Pere-Pau Vázquez, Wolfgang Heidrich, Hans-Peter Seidel).- Antialiasing with Line Samples (Thouis R. Jones, Ronald N. Perry).- Comparing Real & Synthetic Scenes using Human Judgements of Lightness (Ann McNamara, Alan Chalmers, Tom Troscianko, Iain Gilchrist).- Interactive Tone Mapping (Frédo Durand, Julie Dorsey).- Modeling and Rendering for Realistic Facial Animation (Stephen R. Marschner,Brian Guenter, Sashi Raghupathy).- Real-Time Hair (Jerome Lengyel).- Feature-based Displacement Mapping (Xiaohuan Corina Wang, Jérôme Maillot, Eugene Fiume, Victor Ng-Thow-Hing, Andrew Woo, Sanjay Bakshi).- Soft Shadow Maps for Linear Lights (Wolfgang Heidrich, Stefan Brabec, Hans-Peter Seidel).- Hardware Accelerated Horizon Mapping (Peter-Pike J. Sloan, Michael F. Cohen).- General calculations using graphics hardware with applications to interactive caustics (Chris Trendall, A. James Stewart).- Dynamic Acceleration Structures for Interactive Ray Tracing (Erik Reinhard, Brian Smits, Chuck Hansen).- Direct Ray Tracing of Displacement Mapped Triangles (Brian Smits, Peter Shirley, Michael M. Stark).- Ray Tracing Point Sampled Geometry (Gernot Schaufler, Henrik Wann Jensen).- Tapestry: A Dynamic Mesh-based Display Representation for Interactive Rendering (Maryann Simmons, Carlo H. Séquin).- Rendering Iridescent Colors of Optical Disks (Yinlong Sun, F. David Fracchia, Mark S. Drew, Thomas W. Calvert).- A Physically-Based BRDF Model for Multilayer Systems with Uncorrelated Rough Boundaries (Isabelle Icart, Didier Arquès).- Interactive Rendering with Real-World Illumination (Simon Gibson, Alan Murta).- Walkthroughs with Corrective Texturing (Marc Stamminger, Jorg Haber, Hartmut Schirmacher, Hans-Peter Seidel)

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Book SynopsisThe two-volume set LNCS 10269 and 10270 constitutes the refereed proceedings of the 20th Scandinavian Conference on Image Analysis, SCIA 2017, held in Tromsø, Norway, in June 2017. The 87 revised papers presented were carefully reviewed and selected from 133 submissions. The contributions are structured in topical sections on history of SCIA; motion analysis and 3D vision; pattern detection and recognition; machine learning; image processing and applications; feature extraction and segmentation; remote sensing; medical and biomedical image analysis; faces, gestures and multispectral analysis.Table of ContentsHistory of SCIA.- Motion analysis and 3D vision.- Pattern detection and recognition.- Machine learning.- Image processing and applications.- Feature extraction and segmentation.- Remote sensing.- Medical and biomedical image analysis.- Faces, gestures and multispectral analysis.

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